Simultaneous Localization and Mapping for robot navigation
Autonomous navigation encompasses the algorithms and sensor systems that enable robots to move safely and efficiently through environments without human guidance. SLAM (Simultaneous Localization and Mapping) is the core technique, combining sensor data from LiDAR, cameras, IMUs, and GPS to build real-time maps and localize the robot within them. The field is mature for structured indoor environments (warehouses, hospitals) and rapidly advancing for outdoor and dynamic environments.
Autonomous navigation is the foundational capability that enables all mobile robot applications. The maturation of ROS 2 and commercial navigation stacks is dramatically reducing development time, enabling more companies to deploy mobile robots without building navigation from scratch.